Master Thesis – Development of Multi-Modal Perception System for Road Topography Estimation (m/f/d)

TN Germany; Stuttgart; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

Join a leading automotive technology company as a Master Thesis student, working on innovative algorithms for road topography estimation. Collaborate with experts and gain hands-on experience in hardware integration and machine learning. This role offers a unique opportunity to contribute to cutting-edge research while developing practical solutions in the automotive field.

Leistungen

Remote work options

Qualifikationen

• Enrolled in a Master’s program in a relevant field.
• Strong programming skills in Python with experience in relevant libraries.

Aufgaben

• Design and implement algorithms for road topography prediction.
• Develop an integrated hardware system using LiDAR and a camera.

Kenntnisse

Python

Computer Vision

Deep Learning

Problem Solving

Ausbildung

Master’s program in Mechatronics

Master’s program in Computer Science

Master’s program in Electrical Engineering

Tools

OpenCV

NumPy

TensorFlow

PyTorch

Jobbeschreibung

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Master Thesis – Development of Multi-Modal Perception System for Road Topography Estimation (m/f/d), Stuttgart

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Client:

Location:

Stuttgart, Germany

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

98192d9ccfc2

Job Views:

1

Posted:

16.05.2025

Expiry Date:

30.06.2025

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Job Description:

At CARIAD, we're bundling and further expanding the Volkswagen Group's software expertise. We’re uniting over 6,500 global experts to build a scalable technology stack, including a software platform, unified electronic architecture, and reliable connection to the automotive cloud. Our CARIDIANS are developing vehicle functions such as driver assistance systems, a next-generation infotainment platform, power electronics and charging technology, and digital services in and around the vehicle.

Our software can already be found in Volkswagen ID. models and will soon power Audi and Porsche vehicles with the E3 1.2 platform in 2024.

It's no easy task, but with experts like you, we can shape the future of mobility. Join us at CARIAD and be part of this exciting journey!

YOUR TEAM

Our "Chassis" team is seeking a Master thesis student to collaborate with a PhD student on developing an innovative algorithm for predicting road topography using monocular vision. The core research question is: How accurately can texture-less road surfaces be predicted using monocular vision?

As part of our team, you’ll be involved in cutting-edge research, helping to advance powertrain, chassis, and charging functions on a high-performance computing platform. Our applications focus on driving dynamics, optimized charging, and predictive maintenance. A key research area includes controlling active damping systems based on perceived road topography to maximize driver comfort through adaptive control mechanisms.

This thesis offers a hands-on opportunity to build and test your own system using LiDAR and a camera, allowing you to evaluate the algorithm in real-world applications. You will also delve into hardware system development, explore modern depth estimation techniques, and investigate machine learning approaches.

Join us and gain invaluable experience in the field of automotive technology!

WHAT YOU WILL DO

• Design and implement selected algorithms
• Develop an integrated hardware system using LiDAR and a camera to test the algorithm in a vehicle
• Analyze and evaluate the algorithms using real-world data
• Document and present findings for your final thesis
• Prepare and present the results in a scientific paper

WHO YOU ARE

• Enrolled in a Master’s program in Mechatronics, Computer Science, Electrical Engineering, or a related field
• Strong programming skills in Python, with experience in libraries such as OpenCV and NumPy; familiarity with TensorFlow or PyTorch is a plus
• Understanding of computer vision and deep learning concepts; knowledge of advanced architectures (transformers) is a plus
• Hands-on experience with data processing and algorithm development
• Team-oriented, communicative, and proactive in problem-solving
• Interest in hardware integration and automotive engineering is a plus

NICE TO KNOW

• Remote work options
• Duration: 6 months
• If you have further questions about the candidate journey at CARIAD, please contact us: